Keynote Speaker: Dr. Juan Antonio Corrales (Marie Curie University, France)Abstract: In this talk, I will present the audience the Robot Operating System (ROS) framework in a general and introductory way. First of all, I will describe what ROS is, its importance for current academic research in robotics and industry and several of its applications. Afterwards, I will introduce the main concepts (nodes, services, topics, packages, messages, bags, actionlibs, etc.) which constitute the basis of the ROS system and how to use them. All these concepts will be very useful for following the next sessions of the workshop.

Keynote Speaker: Dr. Sachin Chitta (SRI International, USA)Abstract: In this talk, I will walk the audience through the process of installing, configuring and using MoveIt! for motion planning with manipulators in ROS. Topics that will be covered and demoed live include installing MoveIt!, configuring MoveIt! for a new robot, interacting with a robot using the MoveIt! motion planning plugin, executing simple motion plans on a new robot, integrating with controllers, integrating with perception, cartesian motion and scripting tasks.

Keynote Speaker: Dr. Guillaume Walck (University of Bielefeld, Germany)Abstract: ROS and MoveIt! make easier to write a manipulation application for a new robot. However, when an anthropomorphic dexterous hand replaces a simple gripper, some additional steps are required to correctly perform object manipulation and extend it to in-hand manipulation. This talk will highlight pre-requests to using MoveIt! for manipulation with a dexterous hand, and show the possibilities of ROS and MoveIt! in the case of in-hand manipulation.

Keynote Speaker: Dr. Federico Tombari (University of Bologna-Italy, Italy / Open Perception, Inc., USA)Abstract: The Point Cloud Library (PCL) is a large scale, open project for 2D/3D image and point cloud. Among the several modules available in PCL, this talk will focus on those aimed at the task of 3D object recognition in clutter. To this goal, it will address several related aspects such as 3D keypoint detection and description, correspondence grouping and hypothesis verification. Moreover, we will go over a code tutorial explaining how to assemble together the introduced methodologies within a complete object recognition pipeline.